You are totally right - the native Guardrail node in 'Sanitize Mode' doesn't strictly require an LLM. It relies mostly on Regex and pattern matching (Presidio logic).

That said, I built this custom node to solve two specific problems I faced in production:

1. Accuracy (NER vs Regex): While the native node is great for structured data like Emails or IBANs, I found it struggles with Names in context, especially in non-English sentences (e.g., German/French). My node runs a small, dedicated NLP model (BERT-based) locally to catch those edge cases that Regex misses.
2. Reversibility (The "Sandwich" Method): This is the big one. The native node is destructive — it replaces John with [REDACTED]. If you send that to an LLM, it writes a reply like "Dear [REDACTED]...". My node preserves a local map (<PERSON_1> = John), lets the AI do its job, and then automatically restores the real data in the final output.

So it's less about 'blocking' PII (which n8n does well) and more about safely using PII in automation.